Cognitive radios is one of the hot topics for emerging and future wireless commu- nication. It has been proposed as a suitable solution for the spectrum scarcity caused by the increase in frequency demand. The concept is based on allowing unlicensed users, called cognitive or secondary users, to share the unoccupied frequency bands with their owners, called the primary users, under constraints on the interference they cause to them. The objective of our work is to propose some enhancements to cognitive radio systems while taking into account practical constraints. Cogni- tive radios requires a capability to detect spectrum holes (spectrum sensing) and a scheduling flexibility to avoid the occupied spectrum and selectively use the empty spectrum (dynamic resource allocation). Thus, the work is composed of two main parts. The first part focuses on cooperative spectrum sensing. We compute in this part the analytical performance of cooperative spectrum sensing under non identical and imperfect channels. Different schemes are considered for the cooperation between users such as hard binary, censored information, quantized, and soft information. The second part focuses on the dynamic resource allocation. We first propose low-cost re- source allocation algorithms that use location information to estimate the interference to primary users to replace absence of instantaneous channel state information. We extend these algorithms to handle practical implementation constraints such as dis- 5 crete bit-loading and collocated subcarriers allocations. We then propose a reduced dimension approach based on the grouping of subcarriers into clusters and performing the resource allocation over clusters of subcarriers instead of single subcarriers. This approach is shown to reduce the computational complexity of the algorithm with lim- ited performance loss. In addition, it is valid for a generic set of resource allocation problems in presence of co-channel interference between users.

The global value creation networks have experienced increased volatility and dynamic behavior in recent years, resulting in an acceleration of a trend already evident in the shortening of product and technology cycles. In addition, the manufacturing industry is demonstrating a trend of allowing customers to make specific adjustments to their products at the time of ordering. Not only do these changes require a high level of flexibility and adaptability from the cyber-physical systems, but also from the employees and the supervisory production planning. As a result, the development of control and monitoring mechanisms becomes more complex. It is also necessary to adjust the production process dynamically if there are unforeseen events (disrupted supply chains, machine breakdowns, or absences of staff) in order to make the most effective and efficient use of the available production resources. In recent years, reinforcement learning (RL) research has gained increasing popularity in strategic planning as a result of its ability to handle uncertainty in dynamic environments in real time. RL has been extended to include multiple agents cooperating on complex tasks as a solution to complex problems. Despite its potential, the real-world application of multi-agent reinforcement learning (MARL) to manufacturing problems, such as flexible job-shop scheduling, has been less frequently approached. The main reason for this is most of the applications in this field are frequently subject to specific requirements as well as confidentiality obligations. Due to this, it is difficult for the research community to obtain access to them, which presents substantial challenges for the implementation of these tools. ...

Quality-of-Service (QoS) to users is a critical requirement of resource allocation in wireless networks and has drawn significant research attention over a long time. However, the QoS requirements differ vastly based on the wireless network paradigm. At one extreme, we have a millimeter wave small-cell network for streaming data that requires very high throughput and low latency. At the other end, we have Machine-to-Machine (M2M) uplink traffic with low throughput and low latency. In this dissertation, we investigate and solve QoS-aware resource allocation problems for diverse wireless paradigms. We first study cross-layer dynamic spectrum allocation in a LTE macro-cellular network with fractional frequency reuse to improve the spectral efficiency for cell-edge users. We show that the resultant optimization problem is NP-hard and propose a low-complexity layered spectrum allocation heuristic that strikes a balance between rate maximization and fairness of allocation. Next, we develop an energy efficient downlink power control scheme in a energy harvesting small-cell base station equipped with local cache and wireless backhaul. We also study the tradeoff between the cache size and the energy harvesting capabilities. We next analyzed the file read latency in Distributed Storage Systems (DSS). We propose a heterogeneous DSS model wherein the stored data is categorized into multiple classes based on arrival rate of read requests, fault-tolerance for storage etc. Using a queuing theoretic approach, we establish bounds on the average read latency for different scheduling policies. We also show that erasure coding in DSS serves the dual purpose of reducing read latency and increasing the energy efficiency. Lastly, we investigate the problem of delay-efficient packet scheduling in M2M uplink with heterogeneous traffic characteristics. We classify the uplink traffic into multiple classes and propose a proportionally-fair delay-efficient heuristic packet scheduler. Using a queuing theoretic approach, we next develop a delay optimal multiclass packet scheduler and later extend it to joint medium access control and packet scheduling for M2M uplink. Using extensive simulations, we show that the proposed schedulers perform better than state-of-the-art schedulers in terms of average delay and packet delay jitter. / PHD

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / In clusters and virtualized data centers, the resources must be managed effectively by maximising the SLA fulfilment while minimising the cost. This work proposes a strategy for dynamic resource allocation in virtualized computing environments in order to reduce energy consumption without compromising performance requirements concerning availability and SLA violation. The proposed algorithms, based on classical heuristics, perform virtual machines migration between distinct hosts according to the variation in resources demand. These algorithms were evaluated from measurements in a real environment composed by heterogeneous virtualized hosts. We evaluate their performance in four different scenarios based on the CPU and memory utilization, number of migrations and energy consumption. In general, the results show that the algorithms responsible for consolidation and distribution of virtual machines between hosts are able to reduce energy consumption and dissipate the idle and overload points. / Em clusters e data centers virtualizados, os recursos precisam ser gerenciados com eficÃcia na busca de um trade-off entre a garantia de um atendimento satisfatÃrio à demanda por Qualidade de ServiÃo (QoS) e a reduÃÃo dos custos operacionais por parte dos provedores. Este trabalho propÃe uma estratÃgia para alocaÃÃo dinÃmica de recursos em ambientes computacionais virtualizados com vistas à reduÃÃo do consumo de energia, sem promover sobrecargas que podem comprometer o desempenho dos serviÃos ofertados. Os algoritmos propostos, baseados em heurÃsticas clÃssicas, realizam migraÃÃo de mÃquinas virtuais entre servidores distintos conforme variaÃÃo na demanda por recursos. Estes algoritmos foram verificados e validados por mediÃÃes em um ambiente real composto por servidores virtualizados heterogÃneos. O desempenho da proposta à avaliado em quatro cenÃrios distintos a partir das mÃtricas utilizaÃÃo de CPU, utilizaÃÃo de memÃria, nÃmero de migraÃÃes e consumo de energia. Os resultados mostraram que os algoritmos responsÃveis pela consolidaÃÃo e distribuiÃÃo das mÃquinas virtuais sÃo capazes de reduzir o consumo de energia e dissipar os pontos de Ãcio e sobrecarga do ambiente.

Hoy en día existen varias tecnologías que coexisten en una misma zona formando un sistema heterogéneo. Además, este hecho se espera que se vuelva más acentuado con todas las nuevas tecnologías que se están estandarizando actualmente. Hasta ahora, generalmente son los usuarios los que eligen la tecnología a la que se van a conectar, ya sea configurando sus terminales o usando terminales distintos. Sin embargo, esta solución es incapaz de aprovechar al máximo todos los recursos. Para ello es necesario un nuevo conjunto de estrategias. Estas estrategias deben gestionar los recursos radioeléctricos conjuntamente y asegurar la satisfacción de la calidad de servicio de los usuarios. Siguiendo esta idea, esta Tesis propone dos nuevos algoritmos. El primero es un algoritmo de asignación dinámica de recusos conjunto (JDRA) capaz de asignar recursos a usuarios y de distribuir usuarios entre tecnologías al mismo tiempo. El algoritmo está formulado en términos de un problema de optimización multi-objetivo que se resuelve usando redes neuronales de Hopfield (HNNs). Las HNNs son interesantes ya que se supone que pueden alcanzar soluciones sub-óptimas en cortos periodos de tiempo. Sin embargo, implementaciones reales de las HNNs en ordenadores pierden esta rápida respuesta. Por ello, en esta Tesis se analizan las causas y se estudian posibles mejoras. El segundo algoritmo es un algoritmo de control de admisión conjunto (JCAC) que admite y rechaza usuarios teniendo en cuenta todas las tecnologías al mismo tiempo. La principal diferencia con otros algorimos propuestos es que éstos últimos toman las dicisiones de admisión en cada tecnología por separado. Por ello, se necesita de algún mecanismo para seleccionar la tecnología a la que los usuarios se van a conectar. Por el contrario, la técnica propuesta en esta Tesis es capaz de tomar decisiones en todo el sistema heterogéneo. Por lo tanto, los usuarios no se enlazan con ninguna tecnología antes de ser admitidos. / Calabuig Soler, D. (2010). Common Radio Resource Management Strategies for Quality of Service Support in Heterogeneous Wireless Networks [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/7348 / Palancia

Network densification has become a dominant theme for capacity enhancement in cellular networks. However, it increases the operational complexity and expenditure for mobile network operators. Consequently, the essential features of Self-Organising Networks (SON) are considered to ensure the economic viability of the emerging cellular networks. This thesis focuses on quantifying the benefits of self-organisation in Cloud Radio Access Network (C-RAN) by proposing a flexible, energy efficient, and capacity optimised system. The Base Band Unit (BBU) and Remote Radio Head (RRH) map is formulated as an optimisation problem. A self-optimised C-RAN (SOCRAN) is proposed which hosts Genetic Algorithm (GA) and Discrete-Particle-Swarm-Optimisation algorithm (DPSO), developed for optimisation. Computational results based on different network scenarios demonstrate that DPSO delivers excellent performances for the key performance indicators compared to GA. The percentage of blocked users is reduced from 10.523% to 0.409% in a medium sized network scenario and 5.394% to 0.56% in a vast network scenario. Furthermore, an efficient resource utilisation scheme is proposed based on the concept of Cell Differentiation and Integration (CDI). The two-stage CDI scheme semi-statically scales the number of BBUs and RRHs to serve an offered load and dynamically defines the optimum BBU-RRH mapping to avoid unbalanced network scenarios. Computational results demonstrate significant throughput improvement in a CDI-enabled C-RAN compared to a fixed C-RAN, i.e., an average throughput increase of 45.53% and an average blocked users decrease of 23.149% is experienced. A power model is proposed to estimate the overall power consumption of C-RAN. Approximately 16% power reduction is calculated in a CDI-enabled C-RAN when compared to a fixed C-RAN, both serving the same geographical area. Moreover, a Divide-and-Sort load balancing scheme is proposed and compared to the SOCRAN scheme. Results show excellent performances by the Divide-and-Sort algorithm in small networks when compared to SOCRAN and K-mean clustering algorithm.

Cloud computing is an emerging trend where clients are billed for services on a pay-per-use basis. Service level agreements define the formal negotiations between the clients and the service providers on common metrics such as processing power, memory and bandwidth. In the case of service level agreement violations, the service provider is penalised. From service provider's point of view, providing cloud services efficiently within the negotiated metrics is an important problem. Particularly, in large-scale data center settings, manual administration for resource allocation is not a feasible option. Service providers aim to maximize resource utilization in the data center, as well as, avoiding service level agreement violations. On the other hand, from the client's point of view, the cloud must continuously ensure enough resources to the changing workloads of hosted application environments and services. Therefore, an autonomous cloud manager that is capable of dynamically allocating resources in order to satisfy both the client and the service provider's requirements emerges as a necessity. In this thesis, we focus on the autonomous resource allocation in cloud computing environments. A distributed resource consolidation manager for clouds, called IMPROMPTU, was introduced in our previous studies. IMPROMPTU adopts a threshold based reactive design where each unique physical machine is coupled with an autonomous node agent that manages resource consolidation independently from the rest of the autonomous node agents. In our previous studies, IMPROMPTU demonstrated the viability of Multiple Criteria Decision Analysis (MCDA) to provide resource consolidation management that simultaneously achieves lower numbers of reconfiguration events and service level agreement violations under the management of three well-known outranking-based methods called PROMETHEE II, ELECTRE III and PAMSSEM II. The interesting question of whether more efficient single synthesizing criterion and outranking based MCDA methods exist was left open for research. This thesis addresses these limitations by analysing the capabilities of IMPROMPTU using a comprehensive set of single synthesizing criterion and outranking based MCDA methods in the context of dynamic resource allocation. The performances of PROMETHEE II, ELECTRE III, PAMSSEM II, REGIME, ORESTE, QUALIFEX, AHP and SMART are investigated by in-depth analysis of simulation results. Most importantly, the question of what denotes the properties of good MCDA methods for this problem domain is answered. / Graduate / 0984

Este trabalho tem por objetivo propor uma abordagem para o problema de alocação dinâmica de recursos em ambiente de produção baseada no paradigma de multiagentes. Para tanto, é especificada uma arquitetura multiagente genérica chamada M-DRAP - Multi-agent Dynamic Resource Allocation Planning, a partir da qual podem ser derivados modelos particulares. As principais contribuições deste trabalho compreendem: (i) a definição de uma estratégia que permita o planejamento dinâmico de cada recurso no atendimento as demandas das atividades de produção de forma descentralizada e distribuída, através de uma abordagem orientada a projeto; (ii) a proposição de uma organização social baseada em uma abordagem multiagente orientada a mercado, capaz de propiciar relações de negociação entre agentes autônomos no sentido de atenderem aos seus interesses individuais, contribuindo de forma efetiva para a satisfação dos objetivos e restrições temporais e de custos globais ao sistema de produção como um todo; (iii) a especificação de uma arquitetura multiagente derivada do CIMOSA, representando de forma consistente a estrutura funcional e organizacional de um sistema de produção; (iv) a definição de estratégias baseadas em negociação entre os agentes capazes de propiciarem o tratamento das perturbações que afetam o sistema de produção em tempo real. Como contribuindo associada, e proposta uma metodologia para a modelagem conceitual de sistemas multiagentes para o domínio das aplicações envolvendo modelagem de empresas. / The objective of this work is to propose an approach to the problem of dynamic resource allocation in production systems. A multi-agent reference architecture called M-DRAP - Multi-agent Dynamic Resource Allocation Planning - is specified and described in this thesis. The main contributions of this work are (i) the definition of a decentralised and distributed strategy for dynamic resource allocation planning, using a project oriented approach, (ii) the proposition of a social organisation based on marketoriented behaviour, which considers the necessity of each agent's local plan to converge to an adequate global plan in terms of production costs to the whole system, (iii) the definition of a multi-agent architecture inspired in the CIMOSA reference architecture representing a functional and organisational structure, (iv) the definition of a strategy based on negotiation which propitiates real-time disturbance treatment. As an associated contribution, we propose a methodology to multi-agent systems conceptual modelling adequate to the enterprise modelling domain.

Este trabalho tem por objetivo propor uma abordagem para o problema de alocação dinâmica de recursos em ambiente de produção baseada no paradigma de multiagentes. Para tanto, é especificada uma arquitetura multiagente genérica chamada M-DRAP - Multi-agent Dynamic Resource Allocation Planning, a partir da qual podem ser derivados modelos particulares. As principais contribuições deste trabalho compreendem: (i) a definição de uma estratégia que permita o planejamento dinâmico de cada recurso no atendimento as demandas das atividades de produção de forma descentralizada e distribuída, através de uma abordagem orientada a projeto; (ii) a proposição de uma organização social baseada em uma abordagem multiagente orientada a mercado, capaz de propiciar relações de negociação entre agentes autônomos no sentido de atenderem aos seus interesses individuais, contribuindo de forma efetiva para a satisfação dos objetivos e restrições temporais e de custos globais ao sistema de produção como um todo; (iii) a especificação de uma arquitetura multiagente derivada do CIMOSA, representando de forma consistente a estrutura funcional e organizacional de um sistema de produção; (iv) a definição de estratégias baseadas em negociação entre os agentes capazes de propiciarem o tratamento das perturbações que afetam o sistema de produção em tempo real. Como contribuindo associada, e proposta uma metodologia para a modelagem conceitual de sistemas multiagentes para o domínio das aplicações envolvendo modelagem de empresas. / The objective of this work is to propose an approach to the problem of dynamic resource allocation in production systems. A multi-agent reference architecture called M-DRAP - Multi-agent Dynamic Resource Allocation Planning - is specified and described in this thesis. The main contributions of this work are (i) the definition of a decentralised and distributed strategy for dynamic resource allocation planning, using a project oriented approach, (ii) the proposition of a social organisation based on marketoriented behaviour, which considers the necessity of each agent's local plan to converge to an adequate global plan in terms of production costs to the whole system, (iii) the definition of a multi-agent architecture inspired in the CIMOSA reference architecture representing a functional and organisational structure, (iv) the definition of a strategy based on negotiation which propitiates real-time disturbance treatment. As an associated contribution, we propose a methodology to multi-agent systems conceptual modelling adequate to the enterprise modelling domain.

Este trabalho tem por objetivo propor uma abordagem para o problema de alocação dinâmica de recursos em ambiente de produção baseada no paradigma de multiagentes. Para tanto, é especificada uma arquitetura multiagente genérica chamada M-DRAP - Multi-agent Dynamic Resource Allocation Planning, a partir da qual podem ser derivados modelos particulares. As principais contribuições deste trabalho compreendem: (i) a definição de uma estratégia que permita o planejamento dinâmico de cada recurso no atendimento as demandas das atividades de produção de forma descentralizada e distribuída, através de uma abordagem orientada a projeto; (ii) a proposição de uma organização social baseada em uma abordagem multiagente orientada a mercado, capaz de propiciar relações de negociação entre agentes autônomos no sentido de atenderem aos seus interesses individuais, contribuindo de forma efetiva para a satisfação dos objetivos e restrições temporais e de custos globais ao sistema de produção como um todo; (iii) a especificação de uma arquitetura multiagente derivada do CIMOSA, representando de forma consistente a estrutura funcional e organizacional de um sistema de produção; (iv) a definição de estratégias baseadas em negociação entre os agentes capazes de propiciarem o tratamento das perturbações que afetam o sistema de produção em tempo real. Como contribuindo associada, e proposta uma metodologia para a modelagem conceitual de sistemas multiagentes para o domínio das aplicações envolvendo modelagem de empresas. / The objective of this work is to propose an approach to the problem of dynamic resource allocation in production systems. A multi-agent reference architecture called M-DRAP - Multi-agent Dynamic Resource Allocation Planning - is specified and described in this thesis. The main contributions of this work are (i) the definition of a decentralised and distributed strategy for dynamic resource allocation planning, using a project oriented approach, (ii) the proposition of a social organisation based on marketoriented behaviour, which considers the necessity of each agent's local plan to converge to an adequate global plan in terms of production costs to the whole system, (iii) the definition of a multi-agent architecture inspired in the CIMOSA reference architecture representing a functional and organisational structure, (iv) the definition of a strategy based on negotiation which propitiates real-time disturbance treatment. As an associated contribution, we propose a methodology to multi-agent systems conceptual modelling adequate to the enterprise modelling domain.